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Abstract

We have successfully imaged the retinal tumor in a mouse model using an ultra-high resolution spectral-domain optical coherence tomography (SD-OCT) designed for small animal retinal imaging. For segmentation of the tumor boundaries and calculation of the tumor volume, we developed a novel segmentation algorithm. The algorithm is based on parametric deformable models (active contours) and is driven by machine learning-based region classification, namely a Conditional Random Field. With this algorithm we are able to obtain the tumor boundaries automatically, while the user can specify additional constraints (points on the boundary) to correct the segmentation result, if needed. The system and algorithm were successfully applied to studies on retinal tumor progression and monitoring treatment effects quantitatively in a mouse model of retinoblastoma.

OCT images of the retina of a LHβTag transgenic mouse as control in the longitudinal study. The images are located at the same position on the registered fundus and were acquired at the 10th (a, View 2), 11th (b, View 3), and 12th (c, View 4) week of age. The estimated tumor boundaries of the OCT images (a), (b), and (c) by using our segmentation method are shown in (d), (e), and (f), respectively.

OCT cross-sectional images of the retina of a LHβTag transgenic mouse treated with SU1498 in the longitudinal study. The images are located at the same position on the registered fundus and acquired at the 10th (a, View 5), 11th (b, View 6), and 12th (c, View 7) week. The estimated tumor boundaries in (a), (b), and (c) by using our segmentation method are shown in (d), (e), and (f), respectively.

(a) The region of the tumor is selected and highlighted by a yellow box; (b) The result of the segmentation is displayed and no corrections to the estimated boundary were needed. (C) – (F) Example when the tumor was not segmented 100% satisfactorily. (c) The tumor region is selected by a yellow box on the OCT image; (d) The estimated boundary in the upper right region of the tumor is not accurate due to missing contrast between the tumor and the surrounding region; (e) Manual adjustment (yellow line) allowed to correct the estimated boundary and the final result is displayed in (f).

Progressive growth of the tumor size in the retina of the control mouse and the mouse treated with SU1498. Tumor volume was measured at three different stages of the disease: the 10th, 11th and 12th week of age.

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